How to use the tensorflowjs.converters.keras_h5_conversion.write_artifacts function in tensorflowjs

h5_file = h5py.File(h5_path)
  if 'layer_names' in h5_file.attrs:
    model_json = None
    groups = conversion.h5_weights_to_tfjs_format(
        h5_file, split_by_layer=split_weights_by_layer)
  else:
    model_json, groups = conversion.h5_merged_saved_model_to_tfjs_format(
        h5_file, split_by_layer=split_weights_by_layer)

  if output_dir:
    if os.path.isfile(output_dir):
      raise ValueError(
          'Output path "%s" already exists as a file' % output_dir)
    if not os.path.isdir(output_dir):
      os.makedirs(output_dir)
    conversion.write_artifacts(
        model_json, groups, output_dir, quantization_dtype,
        weight_shard_size_bytes=weight_shard_size_bytes)

  return model_json, groups

h5_file = h5py.File(h5_path)
  if 'layer_names' in h5_file.attrs:
    model_json = None
    groups = conversion.h5_weights_to_tfjs_format(
        h5_file, split_by_layer=split_weights_by_layer)
  else:
    model_json, groups = conversion.h5_merged_saved_model_to_tfjs_format(
        h5_file, split_by_layer=split_weights_by_layer)

  if output_dir:
    if os.path.isfile(output_dir):
      raise ValueError(
          'Output path "%s" already exists as a file' % output_dir)
    if not os.path.isdir(output_dir):
      os.makedirs(output_dir)
    conversion.write_artifacts(
        model_json, groups, output_dir, quantization_dtype,
        weight_shard_size_bytes=weight_shard_size_bytes)

  return model_json, groups